Platform-level Indicators of Application Performance

ABSTRACT

A method for monitoring performance includes monitoring packet traffic on at least one socket that is associated with an application running on a computer and is communicated over a data network. First and second instances of a performance indicator of the packet traffic are measured respectively during first and second monitoring intervals. An alert is issued upon making a determination that a change between the first instance and the second instance exceeds a predetermined threshold.

BACKGROUND OF THE INVENTION

The present invention relates generally to computer system management,and specifically to monitoring computing machines without a prioriknowledge of the applications running on the machines.

Virtual machine computing simplifies the use of computing resources byelevating the level of abstraction, which benefits resource providers.Server virtualization is typically used to make more efficient use ofserver resources, to improve server availability, and to centralizeserver administration. Server virtualization masks server resources,such as the identity of individual physical servers and processors, fromserver users. Furthermore, with the advent of freeze-dried softwarestacks, virtualization also has the potential to mask the operatingsystem.

A single physical server is usually divided into multiple isolatedvirtual environments.

The use of virtual computers (generally referred to as “virtualmachines”) to enhance computing power has been known for severaldecades. For example, a classic system, VM, produced by the IBMCorporation, enabled multiple users to concurrently use a singlecomputer by running multiple copies of the operating system. Virtualcomputers have been realized on many different types of computerhardware platforms, including both single-processor and multi-processorunits.

Monitoring the status of applications running on a distributed networktypically includes passive network monitoring or a combination ofapplication-level and passive network monitoring. Data flows areidentified and data is collected on a per-flow or per-application basis,enabling calculation of performance metrics. Collecting and publishingper-flow network data is typically performed using standards such asinternet protocol flow information export (IPFIX) and Netflow™.

SUMMARY

An embodiment of the present invention provides a method for monitoringperformance in which packet traffic is monitored on at least one socketthat is associated with an application running on a computer and iscommunicated over a data network. First and second instances of aperformance indicator of the packet traffic are respectively measuredduring first and second monitoring intervals. Upon making adetermination that a change between the first instance and the secondinstance exceeds a predetermined threshold, an alert is issued.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

For a better understanding of the present invention, reference is madeto the detailed description of the invention, by way of example, whichis to be read in conjunction with the following drawings, wherein likeelements are given like reference numerals, and wherein:

FIG. 1 is a block diagram that schematically illustrates a system thatis monitored by an application performance monitoring system, inaccordance with an embodiment of the present invention;

FIG. 2 is a flow chart of an application performance monitoring method,in accordance with an embodiment of the present invention; and

FIG. 3 is a block diagram that schematically illustrates an applicationperformance monitoring system, in accordance with an alternateembodiment of the present invention.

DETAILED DESCRIPTION

In the following description, numerous specific details are set forth inorder to provide a thorough understanding of the present invention. Itwill be apparent to one skilled in the art, however, that the presentinvention may be practiced without these specific details. In otherinstances, well-known circuits, control logic, and the details ofcomputer program instructions for conventional algorithms and processeshave not been shown in detail in order not to obscure the presentinvention unnecessarily.

As will be appreciated by one skilled in the art, the present inventionmay be embodied as a system, method or computer program product.Accordingly, the present invention may take the form of an entirelyhardware embodiment, an entirely software embodiment (includingfirmware, resident software, micro-code, etc.) or an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit,” “module” or “system.” Furthermore,the present invention may take the form of a computer program productembodied in any tangible medium of expression having computer usableprogram code embodied in the medium.

Any combination of one or more computer usable or computer readablemedium(s) may be utilized. The computer-usable or computer-readablemedium may be, for example but not limited to, an electronic, magnetic,optical, electromagnetic, infrared, or semiconductor system, apparatus,device, or propagation medium. More specific examples (a non-exhaustivelist) of the computer-readable medium would include the following: anelectrical connection having one or more wires, a portable computerdiskette, a hard disk, a random access memory (RAM), a read-only memory(ROM), an erasable programmable read-only memory (EPROM or Flashmemory), an optical fiber, a portable compact disc read-only memory(CDROM), an optical storage device, a transmission media such as thosesupporting the Internet or an intranet, or a magnetic storage device.Note that the computer-usable or computer-readable medium could even bepaper or another suitable medium upon which the program is printed, asthe program can be electronically captured, via, for instance, opticalscanning of the paper or other medium, then compiled, interpreted, orotherwise processed in a suitable manner, if necessary, and then storedin a computer memory. In the context of this document, a computer-usableor computer-readable medium may be any medium that can contain, store,communicate, propagate, or transport the program for use by or inconnection with the instruction execution system, apparatus, or device.The computer-usable medium may include a propagated data signal with thecomputer-usable program code embodied therewith, either in baseband oras part of a carrier wave. The computer usable program code may betransmitted using any appropriate medium, including but not limited towireless, wireline, optical fiber cable, RF, etc.

Computer program code for carrying out operations of the presentinvention may be written in any combination of one or more programminglanguages, including an object oriented programming language such asJava, Smalltalk, C++ or the like and conventional procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The program code may execute entirely on a user's computer,partly on the user's computer, as a stand-alone software package, partlyon the user's computer and partly on a remote computer or entirely onthe remote computer or server. In the latter scenario, the remotecomputer may be connected to the user's computer through any type ofnetwork, including a local area network (LAN) or a wide area network(WAN), or the connection may be made to an external computer (forexample, through the Internet using an Internet Service Provider).

Embodiments of the present invention are described below with referenceto flowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in acomputer-readable medium that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablemedium produce an article of manufacture including instruction meanswhich implement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer implemented process such that theinstructions which execute on the computer or other programmableapparatus provide processes for implementing the functions/actsspecified in the flowchart and/or block diagram block or blocks.

Overview

Measuring indicators of application performance typically requiresapplication-level knowledge. For example, an application responsemeasurement (ARM) standard provides application management capabilities,including measurement of application availability, performance, usage,and end-to-end transaction response time. In order to use the ARMstandard to monitor an application or to monitor middleware used toexecute the application, an application or middleware programmertypically needs to integrate the application with an ARM standardsoftware development kit (SDK). Integration with the ARM standard SDK orother application monitoring products typically requires effort on thepart of the application or middleware programmer. In addition, theprogrammers usually need to have an understanding of the application tobe monitored.

In an embodiment of the present invention, a human system manager or anautomated management software program may measure indicators of serverapplication performance without requiring knowledge of the serverapplication itself. Rather, it may be sufficient to know that anapplication communicates with clients across sockets via a data networksuch as the Internet, and is the only application sending and receivingdata packets via the sockets in question. In the context of this patentapplication and claims, the term “data network” 0 refers to any networkacross which data may be sent from one computing device to another,including, without limitation, Internet Protocol (IP), Ethernet, andFibre Channel networks. The term “sockets” denotes any end-point of aprocess communication flow, not limited to any particular protocol. Theembodiments described in this patent application focus on environmentsin which a computer system runs a single application, which is anincreasingly common situation in systems that use virtualization andfreeze dried stacks. The use in such systems of virtual appliances orpre-packaged software stacks that include the application, middleware(if necessary) and operating systems is emerging. In this paradigm, onevirtual appliance runs on each virtual machine. In this context theapplication is that virtual appliance.

The human system manager or automated software program may use a monitormodule to monitor the sockets on a server running the application ofinterest, and to gather statistics about packet traffic, including datapackets received and sent on each socket. For example, the monitormodule may take measurements to capture data such as a total number ofpackets received and sent via the data network. In another example, thecontrol data in the packets is analyzed, and the number of openconnections or number of queries per unit time is tracked. An analysismodule analyzes performance indicators in order to learn aboutapplication performance. In one type of analysis, the analysis modulelooks at frequency distributions of the measurements taken by themonitor module. The analysis module identifies inbound and outboundpackets that are received and transmitted by the application. Theanalysis module may also determine the relationship between data packetsreceived and sent by the application as described hereinbelow. It mayalso correlate such performance indicators with other types ofmeasurements. For example, the metric of interest may be defined to bethe mean ratio of service time to CPU utilization, or the mean ratio ofnumber of open network connections to number of transactions processed.

Server applications typically receive requests to perform tasks and thenreturn the results over the data network. Examples of serverapplications include mail servers, web servers, and database servers.One performance indicator, the length of the time interval between arequest and a response to the request, can provide an estimate of theperformance of the application. In addition to considering meanintervals, the performance indicator may comprise other statistics, suchas minimum, maximum, variance, or a given percentile level. In addition,composite measures may be defined, such as mean ratio of service time toCPU utilization. Other performance indicators will occur to those whoare skilled in the art. In the current example, the difference betweenthe number of packets received and the number of packets sent providesan estimate of an information packet mean queue length, as describedhereinbelow. The application may support multiple transaction types,which may cause the analysis module to detect multimodal distribution onthe sockets when analyzing performance.

Changes in the distribution of the time interval and changes in theestimated mean queue length may indicate changes in the performance ofthe application. This inference is particularly useful when monitoringvirtual server applications. Typically, each virtual machine runs asingle server application. However, any type of virtual or real machinethat is identified to have the application running, and to havededicated internet protocol sockets used for communication of packettraffic between the application and its clients may utilize themonitoring process described hereinbelow.

When the distribution changes or the estimated mean queue length grows,reflecting a possible change in application performance, the analysismodule may alert the human system manager or automated managementsoftware program. The human system manager may check to see if aresource needed by the monitored server application, such as availablememory, storage, or processing is in short supply. The human systemmanager may then provide additional resources in order to restore serverapplication performance to a normal operating level.

System Architecture

Reference is now made to FIG. 1, which is a block diagram showing asystem that is monitored by an application performance monitoring system20, in accordance with an embodiment of the present invention.Application performance monitoring system 20 uses a data network 22 toprovide communication links between assorted devices and computerswithin system 20. Data network 22 may comprise an internet protocolnetwork, and may include connections, such as wire, wirelesscommunication links, or fiber optic cables.

A host computer 24 serves a number of clients 26 shown as beingconnected to data network 22. Host computer 24 comprises resources 60that include a memory 28 and a processor 30. Memory 28 may be used byhost computer 24 to store software programs and data objects. Clients 26may be implemented by such devices as personal computers, personaldigital assistants (PDA's), or any suitable computing device, eitherfixed or mobile, so long as the computing device has facilities foraccessing data network 22. A client in this context could also be anapplication running on another host. Clients 26 may use the same ordifferent operating systems in many combinations, and are provided withsuitable memory for executing program instructions that support thefunctions and activities detailed below.

Host computer 24 may provide data, such as database query responses, webpages, and email to clients 26. A application 32 executes on hostcomputer 24. Host computer 24 comprises network sockets 34, each ofwhich is an end-point of a duplex communication link that is mapped to acomputer process such as application 32. Communication between clients26 and host computer 24 on a network, such as data network 22, takesplace via data packets sent and received on network sockets 34. Clients26 submit requests in the form of request data packets sent to hostcomputer 24 for processing by application 32 across data network 22,which are received on network sockets 34. Application 32 replies to therequests by sending responses in the form of corresponding data packetsissued from network sockets 34, routed through data network 22 toclients 26.

A monitor module 36 monitors packet traffic passing through networksockets 34, periodically gathering statistics about data packetsreceived and sent by application 32 running on a host computer 24 toclients 26 as detailed hereinbelow. For example, monitor module 36typically monitors data packet receipt times and exit times ofcorresponding data packets. As will be appreciated by one skilled in theart, monitor module 36 may be embodied as a process, service, orapplication.

An analysis module 38 analyzes the statistics gathered by monitor module36, computing, e.g., a probability distribution of request latencies.Analysis module 38 is typically under local or remote control of asystem administrator 40. As will be appreciated by one skilled in theart, analysis module 38 may be embodied as a process, service, orapplication and in some cases may not be collocated with application 32.

Analysis module 38 calculates a performance indicator to determine theperformance quality of application 32. In the present embodiment,analysis module 38 calculates one performance indicator, latency, bysumming the time a request data packet is enqueued for service byapplication 32, referred to herein as “queue time,” together withservice time as detailed hereinbelow. If the probability distributionfor latency changes, such that queue time grows significantly whilerequest processing time remains constant, analysis module 38 determinesthat there may be a system resource issue on host computer 24. An alertmay then be sent by analysis module 38 to a human system manager or toautomated management software. Analysis can then be performed by thehuman system manager or the management software to determine whichresource needs to be provided or to otherwise optimize the configurationof system 20.

System Administration

System administrator 40 typically configures monitoring frequency andduration, in addition to a delay tolerance for distribution changes. Thenature and purpose of the delay tolerance are disclosed in furtherdetail below. System administrator 40 configures monitor module 36 tomonitor application 32 for a monitoring interval, e.g. one minute. Inanother configuration, system administrator 40 sets a monitoringfrequency, determining how often monitoring should be performed bymonitor module 36. Monitoring by monitor module 36 does not need to becontinuous. In some embodiments system administrator 40 configuresmonitor module 36 to monitor network sockets 34 discontinuously.Additionally or alternatively, monitor module 36 may be configured tomonitor network sockets 34 once the load on host computer 24 reaches apredetermined threshold. For example, monitor module 36 may beconfigured to begin monitoring network sockets 34 once the volume ofdata packets passing through monitored network sockets 34 on hostcomputer 24 reaches a predetermined packet traffic level.

System administrator 40 may vary the monitoring interval or samplingfrequency in order to achieve a required precision. Configuration of alonger monitoring interval or lower sampling frequency typically lowersthe overhead required by monitor module 36, while increasing the delaybefore an alert is raised after a performance drop occurs. Configurationof a shorter monitoring interval or higher sampling frequency typicallyincreases the overhead, while decreasing the delay between theperformance drop and the alert. Precision of the analysis is dependenton fine tuning of the monitoring interval parameter. In general, theparameter should be large enough to satisfy the balanced jobsassumption, i.e., the number of requests that enter the system roughlyequals the number of request that exit the system (see “The Art ofComputer Systems Performance Analysis: Techniques for ExperimentalDesign, Measurement, Simulation, and Modeling,” by Raj Jain(Wiley-Interscience, NY, April 1991, ISBN:0471503361). The notion of“large enough” may differ from system to system, however, and thereforeis a matter of fine tuning that may be performed either manually orautomatically.

System administrator 40 configures analysis module 38, setting the delaytolerance. The delay tolerance accommodates a permissible deviation inmean latency as described below, and defines a range within which datapacket wait time is allowed to vary above a predetermined threshold. Inone configuration, system administrator 40 sets an analysis frequency,determining how often analysis module 38 should analyze statisticsgathered by monitor module 36.

Configuration of the monitoring and analysis modules may also be doneautomatically.

Embodiment 1

Reference is now made to FIG. 2, which is a flow chart of an applicationperformance monitoring method, in accordance with an embodiment of thepresent invention. For convenience and clarity, the method is describedhereinbelow with reference to system 20, shown in FIG. 1, but the methodmay alternatively be carried out in other monitoring and analysisconfigurations. For example, the analysis module used in the method maybe located on a different host from the application being monitored andthe monitor module.

In a performance data monitoring step 42, monitor module 36 monitorsnetwork sockets 34, capturing headers of data packets received by hostcomputer 24 from clients 26 and headers of data packets sent to clients26 by host computer 24 via network sockets 34 during a monitoringinterval. Monitor module 36 may also record data from the data packetheaders, such as a socket identifier, a packet direction, either sent orreceived, and a timestamp. Some communication between application 32 andclients 26 may be in the form of multi-packet messages, also known as“packet trains”, typically when application 32 responds to requests fromclients 26. Monitor module 36 typically records data only from a firstdata packet in a packet train upon identifying the packet train.

In a statistics generating step 44, analysis module 38 generatesstatistics to describe the performance data monitored by monitor module36, typically by calculating a mean queue length (such as the length ofthe request queue), a mean latency, a mean service time, and a meanqueue time over the monitoring interval.

In a statistics analyzing step 46, analysis module 38 analyzes thestatistics generated in statistics generating step 44. The mean queuelength represents a difference between the number of data packetsreceived from clients 26 by host computer 24 and the number of datapackets sent to clients 26 by host computer 24 over a time interval δ<Δ,wherein A denotes the above-mentioned monitoring interval of monitormodule 36. Setting k=Δ/δ to be the number of the smaller time intervalsof duration δ that fit into a single monitoring interval of duration Δgives:

$\begin{matrix}{L = {\frac{{\sum\limits_{i = 1}^{k}p_{r}^{i}} - {\sum\limits_{i = 1}^{k}p_{s}^{i}}}{k}.}} & (1)\end{matrix}$

Here L is mean queue length, p_(r) ^(i) is the number of packetsreceived during time interval i of duration δ, and p_(s) ^(i) is thenumber of packets sent to clients 26 via network sockets 34 byapplication 32 during time interval i of duration δ.

Analysis module 38 uses the second form of Little's law as described,for example, in “The Art of Computer Systems Performance Analysis:Techniques for Experimental Design, Measurement, Simulation, andModeling,” by Raj Jain (Wiley-Interscience, NY, April 1991,ISBN:0471503361), to derive an approximation of the mean queue time,using the approximation of L calculated in the following equation:

$\begin{matrix}{{W = \frac{L}{\lambda}},} & (2)\end{matrix}$

where λ is an average inter-arrival rate and W is the mean queue time.Average arrival rate λ is a directly measured metric, enabling monitormodule 36 to monitor the average arrival rate precisely. As notedhereinabove, monitor module 36 typically records data only from thefirst data packet in monitored packet trains. The average arrival rateis the time between receipt of the request data packet by host computer24 on network sockets 34, and the exit time from network sockets 34 ofthe corresponding data packet sent to clients 26 by application 32,typically containing a response to the request. The approximation of themean queue time derived in Equation 2 may have a measurement errorintroduced by systematic errors inherent in estimating the mean queuelength. However, the measurement error should not affect the analysisperformed by analysis module 38.

Analysis module 38 calculates mean latency using the following equation:

$\begin{matrix}{{T = \frac{{\sum t_{s}} - {\sum t_{r}}}{p_{s}}},} & (3)\end{matrix}$

where T is the mean latency; t_(s) are times at which the data packetcontaining the responses are sent back to clients 26 via network sockets34 by application 32; t_(r) are times at which the data packetcontaining the requests is received by application 32 from clients 26via network sockets 34; and p_(s) is the number of packets received bythe application from clients 26 via network sockets 34 during themonitoring interval Δ. The summation is performed over all requests andresponses logged during the monitoring interval Δ as discussed above.

Analysis module 38 calculates mean service time using the followingequation:

S=T−W   (4),

where S is the mean service time.

In a distribution change decision step 48, analysis module 38 decideswhether the frequency distributions have changed enough to warrantraising an alert. It is necessary to distinguish between a first case inwhich an increase in the mean latency T caused by transactions ofincreased complexity being processed by application 32 leading to anincrease in mean service time S, and a second case in which the increasein the mean latency T is caused by data packets being enqueued forservice for a longer period of time, leading to an increase in meanqueue time W.

Increased transaction complexity is usually considered to be normalbehavior for application 32. However, if mean queue time W has increasedfrom one monitoring interval to the next, while mean service time S hasremained the same, it indicates that there is a problem. For example,there may be an issue with host computer 24, such as a shortage ofrequired resources for application 32.

Analysis module 38 may use the delay tolerance to determine whether asignificant performance change has occurred. System administrator 40 mayconfigure the delay tolerance as described hereinabove in the SystemAdministration section. Alternatively or additionally, the delaytolerance may be automatically adjusted by analysis module 38responsively to the changes in performance measurements. Analysis module38 determines that a performance change has occurred when the mean queuetime W increases from one monitoring interval to the next, while themean service time S remains constant. Analysis module 38 compares thevalues of W and S in previous and current monitoring intervals. If W hasincreased to exceed the delay tolerance, while S has remained unchanged,analysis module 38 raises an alert in an alert raising step 50. Thedelay tolerance delineates the maximum increase by W from one monitoringinterval to the next.

The alert reports that during the monitoring interval of monitor module36, the transactions processed by application 32 executing on hostcomputer 24 took significantly longer than expected. Analysis module 38may communicate the alert to system administrator 40 or to automatedmanagement software. The human manager or automated management softwaremay respond to the alert by taking corrective measures, such asproviding additional resources to host computer 24 or to the computer inquestion such as a virtual machine in the embodiment describedhereinbelow.

If W has increased by less than the delay tolerance, and no alert israised, analysis module 38 waits until elapse of a time interval set bysystem administrator 40 in a performance data rechecking step 52.

Embodiment 2

Reference is now made to FIG. 3 which is a block diagram thatschematically illustrates an application performance monitoring system,in accordance with an alternate embodiment of the present invention. Thediagram is similar to the diagram of FIG. 1, except as described below.

In the embodiment shown in FIG. 3, system 20 supports clients 26 byutilizing a virtual platform that includes a virtual machine manager,implemented as a hypervisor 54, which is typically realized as asoftware program that resides in memory 28. An example of hypervisor 54is Xen™, a free open-source program that allows multiple guest operatingsystems to be executed on the same computer hardware at the same time.Hypervisor 54 interacts with at least one guest operating system 56 ofclients 26 or of host computer 24. Guest operating system 56 controlsone or more virtual machines, which present themselves to guestoperating system 56 as though they were conventional real machines. Inthe example shown in FIG. 3, there are three virtual machines running onhost computer 24, which respectively perform the functions of a servicepartition 58 and virtual servers 62A, 62B (referred to genericallyhereinbelow as server 62). This specific configuration is shown solelyby way of example, and the principles of this embodiment may similarlybe implemented in different virtual machine configurations.

Server 62 may provide data to clients 26. Application 32 executes onserver 62, supported by guest operating system 56, which can be anyconventional operating system, e.g., Microsoft Windows®, Unix®, orLinux®. Server 62 comprises network sockets 34, and communicationbetween clients 26 and server 62 on data network 22 takes place onnetwork sockets 34. In one example, server 62 is a virtual appliancecomprising a freeze-dried software stack, which includes the applicationand guest operating system. The freeze-dried software stack typicallyincludes a single software image of software, configuration, bestpractices and processes. The single software image typically comprisesrequired functions of base products already configured and optimized forspecific hardware platforms and packaged for distribution andmaintenance.

In the embodiment of FIG. 3, monitor module 36 and analysis module 38run on guest operating system 56. As described hereinabove, monitormodule 36 and analysis module 38 may be embodied as processes, services,or applications and may not be collocated with application 32. In theembodiment shown in the figure, monitor module 36 runs in servicepartition 58 and monitors multiple applications running in multipleguest operating systems managed by hypervisor 54. In one example,hypervisor 54 is Xen, and monitor module 36 runs in guest operatingsystem 56 on host computer 24, realized as “domain 0,” which may also bereferred to as the service partition. When Xen is used, a first guestoperating system, typically referred to as domain 0, is bootedautomatically when hypervisor 54 boots and is given special managementprivileges including direct access to the physical hardware. Inalternative embodiments, monitor module 36 can run in hypervisor 54, orit can run in a separate guest operating system on host computer 24,rather than running in the first guest operating system, or domain 0.

Monitor module 36 and analysis module 38 are shown in FIG. 3 as runningon guest operating system 56 for the purpose of clarity. However, it isunderstood that the modules can be distributed among multiple servers,or that server 62 may be realized not only as a plurality of virtualmachines, as shown in the figure, but also as any combination of realand virtual machines.

Embodiment 3

In another embodiment of FIG. 3, monitor module 36 monitors theavailability of resources 60 on virtual machine 58. Resources 60 maycomprise memory, storage space, central processing unit (CPU) cycles,storage bandwidth, network bandwidth, or any other resource used byapplication 32 to process requests from clients 26. When analysis module38 raises the alert as described hereinabove, it may correlateutilization of resources 60 with the performance change using any methodknown to a person who is ordinarily skilled in the art.

One method for correlating resource utilization with performancemeasurements is described in U.S. Patent Publication No. 2006/0293777,whose disclosure is incorporated herein by reference. The methodincludes automatically deriving thresholds for platform-level metricssuch as CPU utilization, storage bandwidth utilization, and memoryutilization. Correlation of resource utilization with performancemeasurements by analysis module 38 may provide an understanding of whichof resources 60 has the most impact on the performance of application32. In some applications resources may be automatically adjustedresponsively to the changes in performance measurements.

It will be appreciated by persons skilled in the art that the presentinvention is not limited to what has been particularly shown anddescribed hereinabove. Rather, the scope of the present inventionincludes both combinations and sub-combinations of the various featuresdescribed hereinabove, as well as variations and modifications thereofthat are not in the prior art, which would occur to persons skilled inthe art upon reading the foregoing description.

1. A method for monitoring performance, comprising: monitoring packettraffic on at least one socket that is associated with an applicationrunning on a computer and is communicated over a data network; measuringa first instance of a performance indicator of the packet traffic duringa first monitoring interval; measuring a second instance of theperformance indicator during a second monitoring interval; making adetermination that a change between the first instance and the secondinstance exceeds a predetermined threshold; and responsively to thedetermination, issuing an alert.
 2. The method according to claim 1,wherein the performance indicator comprises an estimate of mean queuelength associated with the application based on a difference between anumber of packets received and a number of packets sent.
 3. The methodaccording to claim 1, wherein the application runs on a virtual machine.4. The method according to claim 1, wherein the performance indicatorcomprises an average request arrival rate that is obtained byapproximation based on directly measuring a packet inter-arrival rate.5. The method according to claim 1, wherein the performance indicatorcomprises an average queue time obtained by applying Little's law to ameasurement of the packet traffic.
 6. The method according to claim 1,wherein the performance indicator comprises a mean latency obtained fromdifferences in time between sending a response packet and receiving arequest packet.
 7. The method according to claim 6, wherein theperformance indicator comprises a mean service time obtained as adifference between the mean latency and an average queue time obtainedby applying Little's law to a measurement of the packet traffic.
 8. Themethod that according to claim 1, wherein the performance indicatorcomprises a frequency distribution of at least one of a mean servicetime and a mean queue time.
 9. The method according to claim 1, whereinthe steps of measuring a first instance and measuring a second instanceare performed only when the packet traffic exceeds a predeterminedlevel.
 10. The method according to claim 1, further comprising the stepof adjusting a resource of the computer responsively to thedetermination.
 11. The method according to claim 10, wherein adjustingthe resource of the computer comprises automatically adjusting theresource of the computer.
 12. A computer software product for monitoringperformance, comprising a computer storage medium in which computerprogram instructions are stored, which instructions, when executed by aprocessor, cause the processor to monitor packet traffic on at least onesocket that is associated with an application running on a computer andis communicated over a data network, to measure a first instance of aperformance indicator of the packet traffic during a first monitoringinterval, to measure a second instance of the performance indicatorduring a second monitoring interval, to make a determination that achange between the first instance and the second instance exceeds apredetermined threshold, and responsively to the determination, to issuean alert.
 13. The computer software product according to claim 12,wherein the performance indicator comprises an estimate of mean queuelength associated with the application based on a difference between anumber of packets received and a number of packets sent.
 14. Thecomputer software product according to claim 12, wherein the applicationruns on a virtual machine.
 15. The computer software product accordingto claim 12, wherein the instructions cause the processor to measure thefirst instance and to measure the second instance only when the packettraffic exceeds a predetermined level.
 16. The computer software productaccording to claim 12, wherein the instructions cause the processor toadjust a resource of the computer responsively to the determination. 17.A data processing system for monitoring performance comprising: a memoryfor storing programs and data objects; and a processor, which is coupledto access the memory and is configured to monitor packet traffic on atleast one socket that is associated with an application running on acomputer and is communicated over a data network, and to measure a firstinstance of a performance indicator of the packet traffic during a firstmonitoring interval, to measure a second instance of the performanceindicator during a second monitoring interval, to make a determinationthat a change between the first instance and the second instance exceedsa predetermined threshold, and responsively to the determination, toissue an alert.